This paper presents the design and analysis of Neuro-Fuzzy controller based on Adaptive Neuro-Fuzzy inference system (ANFIS) architecture for Load frequency control of interconnected areas, to regulate the frequency deviation and power deviations. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to s...

This paper presents a neuro-fuzzy network where all its parameters can be tuned simultaneously using Genetic Algorithms. The approach combines the merits of fuzzy logic theory, neural networks and genetic algorithms. The proposed neuro-fuzzy network does not require a priori knowledge about the system and eliminates the need for complicated design steps like manual tuning of input-output member...

In this paper, an adaptive control method for hybrid position/force control of robot manipulators, based on neuro-fuzzy modeling, is presented. Since the force control involves applying certain amount of force on the surface of an object, it is important to consider the friction force between the end-effector and the surface into account. In order to compensate this friction force, a robust and...

Abstract This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education....

In this work, an adaptive critic-based neuro-fuzzy is presented for an unmanned bicycle. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the back propagation of error algorithm to tune online conclusion parts of the fuzz...

The purpose of the study is the synthesis of a reliable and robust fuzzy controller for a 2 order DC servodrive. A first step is to prepare the computations associated to the main control loops for the above mentioned servosystem. This approach aims to aggregate the relations for the position and the velocity loops as an unique computation formula expressed into the variables specific for the r...

This paper describes the design and development of a novel controller for a non-linear power electronic converter. Neuro-Fuzzy controller is proposed to improve the performance of the buck &boost converters. The duty cycle of the buck & boost converters are controlled by NeuroFuzzy controller. The conventional PI controllers for such converters, designed under the worst case condition of maximu...

Abstract: In this paper an application of the adaptive neuro-fuzzy inference system has been introduced to predict the behavior of a chaotic robot. The chaotic mobile robot implies a mobile robot with a controller that ensures chaotic motions. Chaotic motion is characterized by the topological transitivity and the sensitive dependence on initial conditions. We have used the controller such that...

Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...

This work introduces an embedded small indoor helicopter heading controller based on fuzzy logic. The work addresses the problem of system identification when implementing a Takagi-Sugeno-Kang type fuzzy logic controller. Instead of identifying the system formally beforehand, the fuzzy controllers consequent parameters are learned using a Neuro-Fuzzy Inference System with data collected from an...